This paper investigates how affective forecasting errors (A.F.E.s), the difference between anticipated emotion and the emotion actually experienced, may induce changes in preferences on time, risk and occupation after combat. Building on psychological theories incorporating the role of emotion in decision-making, we designed a before-and-after-mission survey for Danish soldiers deployed to Afghanistan in 2011. Our hypothesis of an effect from A.F.E.s is tested by controlling for other mechanisms that may also change preferences: immediate emotion, trauma effect – proxied by post-traumatic stress disorder (P.T.S.D.) – and changes in wealth and risk perception. At the aggregate level, results show stable preferences before and after mission. We find positive A.F.E.s for all three emotions studied (fear, anxiety and excitement), with anticipated emotions stronger than those actually experienced. We provide evidence that positive A.F.E.s regarding fear significantly increase risk tolerance and impatience, while positive A.F.E.s regarding excitement strengthen the will to stay in the military. Trauma has no impact on these preferences.

Despite unprecedented progress in developing COVID-19 vaccines, global vaccination levels needed to reach herd immunity remain a distant target, while new variants keep emerging. Obtaining near universal vaccine uptake relies on understanding and addressing vaccine resistance. Simple questions about vaccine acceptance however ignore that the vaccines being offered vary across countries and even population subgroups, and differ in terms of efficacy and side effects. By using advanced discrete choice models estimated on stated choice data collected in 18 countries/territories across six continents, we show a substantial influence of vaccine characteristics. Uptake increases if more efficacious vaccines (95% vs 60%) are offered (mean across study areas = 3.9%, range of 0.6%–8.1%) or if vaccines offer at least 12 months of protection (mean across study areas = 2.4%, range of 0.2%–5.8%), while an increase in severe side effects (from 0.001% to 0.01%) leads to reduced uptake (mean = −1.3%, range of −0.2% to −3.9%). Additionally, a large share of individuals (mean = 55.2%, range of 28%–75.8%) would delay vaccination by 3 months to obtain a more efficacious (95% vs 60%) vaccine, where this increases further if the low efficacy vaccine has a higher risk (0.01% instead of 0.001%) of severe side effects (mean = 65.9%, range of 41.4%–86.5%). Our work highlights that careful consideration of which vaccines to offer can be beneficial. In support of this, we provide an interactive tool to predict uptake in a country as a function of the vaccines being deployed, and also depending on the levels of infectiousness and severity of circulating variants of COVID-19.

Redistributive justice is based on the premise that it is unfair for people to be better or worse off relative to others simply because of their fortune or misfortune. It assumes equal opportunities arising from four factors: social circumstances, effort, option luck and brute luck. This paper seeks to investigate how differences in perceived brute luck influence individual preferences for redistribution in favour of two public policies: “health intervention” and “environmental actions”. These policies are viewed somewhat differently: the environment is considered a pure “public good” and health, more as a “private good” with a strong public good element. Consequently, potential self-serving biases inherent in the preferences for redistributive policies are expected to differ, more likely favouring health than the environment. The perceived degree of brute luck may capture such a difference—those perceiving themselves as luckiest should be less amenable to redistribution in favour of health than the unluckiest. Data from the three waves (2000, 2006 and 2008) of a French population survey are used to examine this self-serving bias. A Generalised Ordered Logit (GOL) model is found to be statistically more relevant compared to other logistic regression models (multinomial and ordered). We find that a perceived low degree of brute luck is significantly associated with a decreased preference of redistributive environmental policies but the reverse is true for redistributive health policies, i.e., association with an increased preference. Assuming that all inequalities due to differing luck are unjust, this empirical validation gives redistributive justice grounds for equalisation policies regarding health.

Cet article propose une approche intégrant le temps de latence dans le processus d’évaluation de la mortalité de long terme et dans sa valorisation économique, suite à un choc transitoire. Il l’applique aux conséquences des restrictions d’activité en lien avec la Covid‑19 au printemps 2020 sur la pollution de l’air ambiant en France. Ces conséquences sont évaluées en termes d’années de vie gagnées (AVG) ainsi qu’en termes monétaires pour deux indicateurs de pollution de l’air. Cette approche est comparée à une estimation standard par différence. Elle conduit à des résultats inférieurs d’un facteur 3.7 à 5.5 pour les AVG et, du fait de l’influence additionnelle de l’actualisation, à une valorisation économique inférieure d’un facteur 4.7 à 6.9. Ces résultats indiquent qu’une évaluation adaptée des bénéfices sanitaires de long terme, puis leur traduction en termes monétaires, est essentielle pour comparer les conséquences à long terme de politiques ou de chocs exogènes transitoires.